Political Spending in the US in 2022 Was 7.5% Lower Than Forecasts

2022 was an important year for the United States of America due to the countless elections that were occurring simultaneously. Election years can be a boon for the ad industry because of the fact that this is the sort of thing that could potentially end up pumping billions dollars into campaigns that seek to promote certain candidates. However, 2022 actually saw this spending miss the mark.

A marketing intelligence firm by the name of AdImpact recently revealed that political ad dollars in the US were 7.5% lower than initially predicted. The forecasted ad spending was at around $9.67 billion, but in spite of the fact that this is the case it fell short by over half a billion dollars to settle at around $8.94 billion instead.

According to estimates, around $1.85 billion was supposed to be spent on House of Representatives races. The final number that was noted ended up being closer to $1.55 billion instead. This shortfall can be seen across the board with almost all types of elections save for downballot races. These were the only elections that ended up exceeding expectations, with the $2.99 billion forecast getting overshadowed by the $3.28 billion final total.

One thing to note here is that some forms of media actually exceeded expectations. Cable news was expected to receive $1.54 billion in ad dollars, which would’ve comprised 15.9% of the projected total. However, when the numbers came, it was found that cable TV received $1.79 billion, and that came up to an impressive 20% of the total ad dollars that came in.

Broadcast television did not perform quite as well. The estimated political ad income for broadcast networks was $4.98 billion, or 51.45% of the total. While broadcast TV was still the biggest player in the arena, it received slightly less than what was predicted with $4.73 billion.

This just goes to show how challenging it can be to make accurate predictions in this regard. AdImpact has stated that it will be using the data from this shortfall to improve the accuracy of future predictions so that they can be used more effectively.


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